GGplot

Thibaut FABACHER

GMRC

Introduction à GGplot 2

Ressource

https://ggplot2-book.org

Installation

GGplot2 est inclu dans le tidyverse . . .

install.packages("tidyverse")

On peut installer uniquement ggplot2 . . .

install.packages("ggplot2")

Ou sa version de développement . . .

install.packages("devtools")
devtools::install_github("tidyverse/ggplot2")

Importation de la librairie

library(ggplot2)

Cheatsheet

Principe de base

ggplot(data = <DATA>, mapping = aes(<MAPPINGS>)) +  <GEOM_FUNCTION>()

Aesthetic mappings` décrit comment les variables de data sont mapper sur des formes géométriques

#Code ne donne rien, juste des données
ggplot(mtcars)

Code un graphiques vides car des données des aesthetic mappings mais pas d’aesthetic

ggplot(mtcars, aes(x= mpg, y = drat ))

Types de graphes

Nuage de points

ggplot(mtcars, aes(x= mpg, y = drat ))+geom_point()

Changement de la taille et la forme

ggplot(mtcars, aes(x=wt, y=mpg)) +
  geom_point(size=2, shape=23)

Shape des points :

Changer la taille des points selon une troisième variable

ggplot(mtcars, aes(x=wt, y=mpg)) + 
  geom_point(aes(size=qsec))

ggplot(mtcars, aes(x=wt, y=mpg, size=qsec)) + 
  geom_point()

Rajouter une variable groupe :

Types de points

mtcars$cyl<- as.factor(mtcars$cyl)
ggplot(mtcars, aes(x=wt, y=mpg, shape=cyl)) +
  geom_point()

Type et couleur

ggplot(mtcars, aes(x=wt, y=mpg, shape=cyl, color=cyl)) +
  geom_point()

Type, couleur et taille

ggplot(mtcars, aes(x=wt, y=mpg, shape=cyl, color=cyl, size=cyl)) +
  geom_point()

scales

Les scales permettent de modifier les axes x et y Par défaut R en ajoute pour chaque aesthetic

ggplot(mpg, aes(displ, hwy)) + 
  geom_point(aes(colour = class)) +
  scale_x_continuous() + 
  scale_y_continuous() + 
  scale_colour_discrete()

Modification des noms des axes

ggplot(mpg, aes(displ, hwy)) + 
  geom_point(aes(colour = class)) + 
  scale_x_continuous(name = "A really awesome x axis label") +
  scale_y_continuous(name = "An amazingly great y axis label")

#> Scale for 'x' is already present. Adding another scale for 'x', which will
#> replace the existing scale.

Définitions des limites des axes

ggplot(mpg, aes(displ, hwy)) + 
  geom_point()+  
  scale_x_continuous(limits = c(1, 7)) +
  scale_y_continuous(limits = c(10, 45))

!!! Attention, tronques les données

Zoom

library(gridExtra)
base <- ggplot(mpg, aes(drv, hwy)) + 
  geom_hline(yintercept = 28, colour = "red") + 
  geom_boxplot() 
grid.arrange(
base,
base + coord_cartesian(ylim = c(10, 35)), # works as expected
base + ylim(10, 35) ,
ncol = 3)

Transformation de l’échelle

# log transform x and y axes
ggplot(diamonds, aes(price, carat)) + 
  geom_bin2d() + 
  scale_x_continuous(trans = "log10") +
  scale_y_continuous(trans = "log10")

Couleurs des échelles

Echelles continues

erupt <- ggplot(faithfuld, aes(waiting, eruptions, fill = density)) +
  geom_raster() +
  scale_x_continuous(name = NULL, expand = c(0, 0)) + 
  scale_y_continuous(NULL, expand = c(0, 0)) + 
  theme(legend.position = "none")
erupt

Modification de la couleur

palettes pré spécifiées

grid.arrange(
erupt,
erupt + scale_fill_viridis_c(),
erupt + scale_fill_viridis_c(option = "magma"),
ncol = 3 )

grid.arrange(
erupt + scale_fill_distiller(),
erupt + scale_fill_distiller(palette = "RdPu"),
erupt + scale_fill_distiller(palette = "YlOrBr"),
ncol = 3)

Autres couleurs

packages : scico, paletteer, wesanderson,
Spécifier des dégradés : scale_color_gradient(), scale_color_gradient2(), scale_color_gradientn()
palette manuelle : scale_fill_manual(values = c(“#000000”, “#E69F00”, “#56B4E9”, “#009E73”,“#F0E442”, “#0072B2”, “#D55E00”, “#CC79A7”))

https://www.datanovia.com/en/fr/blog/couleurs-ggplot-meilleures-astuces-que-vous-allez-adorer/

L’aes à changer :

scale_fill_discrete()
scale_color_discrete()
scale_color_manual()
…

Thèmes

Spécifie les éléments non en rapport avec les données

labelled <- base +
  labs(
    x = "City mileage/gallon",
    y = "Highway mileage/gallon",
    colour = "Cylinders",
    title = "Highway and city mileage are highly correlated"
  ) +
  scale_colour_brewer(type = "seq", palette = "Spectral")

labelled_stylise <-  labelled+ theme_bw() + 
  theme(
    plot.title = element_text(face = "bold", size = 12),
    legend.background = element_rect(fill = "white", size = 4, colour = "white"),
    legend.justification = c(0, 1),
    legend.position = c(0, 1),
    axis.ticks = element_line(colour = "grey70", size = 0.2),
    panel.grid.major = element_line(colour = "grey70", size = 0.2),
    panel.grid.minor = element_blank()
)

grid.arrange(labelled,labelled_stylise, ncol = 2)

Thème de base :

theme_bw(): a variation on theme_grey() that uses a white background and thin grey grid lines.
theme_linedraw(): A theme with only black lines of various widths on white backgrounds, reminiscent of a line drawing.

- `theme_light()`: similar to `theme_linedraw()` but with light grey lines and axes, to direct more attention towards the data.
- `theme_minimal()`: A minimalistic theme with no background annotations.
- `theme_classic()`: A classic-looking theme, with x and y axis lines and no gridlines.

theme_void(): A completely empty theme.

df <- data.frame(x = 1:3, y = 1:3)
base <- ggplot(df, aes(x, y)) + geom_point()
grid.arrange(
base + theme_grey() + ggtitle("theme_grey()"),
base + theme_bw() + ggtitle("theme_bw()"),
base + theme_linedraw() + ggtitle("theme_linedraw()"),
ncol = 3)

library(ggthemes)
grid.arrange(
base + theme_tufte() + ggtitle("theme_tufte()"),
base + theme_solarized() + ggtitle("theme_solarized()"),
base + theme_excel() + ggtitle("theme_excel()"),
ncol = 3)

Assistance création de thème

ggThemeAssist